dc.description.abstract | Child mortality refers to death of a child between 0 and ve years old. Kenya like many
Sub-Saharan countries faces a burden of child mortality, and has made e orts towards
reducing the same. The main The main objective of the study is to evaluate the spatial
variation in under- ve mortality in Kenya using spatial survival methods.
Methods
Data on child mortality was collected through the Demographic Health Survey 2014. The
survey collected information on children, demographic indicators related to the mother
and child, and various social and economic attributes. Intrinsic Conditional Autoregressive
Models were tted to account for spatial dependence and clustering to estimate the
hazard at county level, together with a cox-proportional hazard model to estimate the risk
factors associated with child mortality.
Results
The spatial cox proportional hazard model was identi ed as the best t based of the Deviance
Information Criterion (DIC). There exists a spatial structure on the hazard of death
in the Kenyan counties. Counties with the highest hazard of death include counties around
central Kenya (Laikipia, Nyandarua, Nyeri, Kiambu, Machakos and Makueni), although
most counties have similar hazards. The lowest hazard is found in Western Kenya counties
and Nyanza. Sex of the child, sex of household head, age of respondent at rst birth,
level of education, and whether a child is in a multiple birth are signi cant risk factors of
child mortality.
Conclusion
This study brings out the spatial disparities that exist in the country on child mortality
in Kenya. The speci c counties have mortality rates that are county-speci c, with neighbouring
counties having similar hazards for death of a child. is important therefore for
interventions to take into consideration the e ect of where a child is born(county) to reduce
mortality. | en_US |